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Incorporating Time–Dose–Response Into Shigella flexneri and Shigella sonnei Outbreak Models
Author(s) -
Prasad Bidya,
Haas Charles N.
Publication year - 2017
Publication title -
journal ‐ american water works association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 74
eISSN - 1551-8833
pISSN - 0003-150X
DOI - 10.5942/jawwa.2017.109.0150
Subject(s) - shigella sonnei , shigella flexneri , weibull distribution , outbreak , poisson distribution , log normal distribution , incubation period , shigella , mathematics , statistics , incubation , biology , virology , escherichia coli , biochemistry , gene
Experimental time‐to‐infection data are a useful but often underused material for examining the mechanics of in vivo pathogen growth. The authors incorporated a time–dose–response (TDR) equation into a Shigella flexneri outbreak model. Dose–response and TDR models were generated for Shigella sonnei outbreak model. Dose–response and TDR models were generated for S. flexneri exposure to monkeys. The TDR equation that best fit the monkey data—the beta‐Poisson with exponential dependency model—was chosen for incorporation into the outbreak model. The outbreak model is a probability model that convolutes an assumed incubation distribution of the infectious agent with an exposure distribution. Since the beta‐Poisson with exponential dependency models the time‐to‐infection density distribution, it is entered as the incubation distribution, along with Weibull, lognormal, gamma, and uniform functions. Each of these five incubation functions is convoluted with Weibull, lognormal, gamma, and uniform functions (which served as exposure distributions) for a total of 20 models. The time‐dependent probability distribution yielded best‐fit results for the S. sonnei outbreak scenario.